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Major compute price reduction on Neon

Reducing cost of compute by 25% as we scale on Databricks

Joining Databricks has fast-forwarded our scaling journey by at least an order of magnitude. A side-effect of that is decreased costs from efficiency of scale. We're passing this directly to customers. (Remember when AWS did that?) Starting with the November billing period, we've decreased the cost of compute on Neon by up to 25%.

Launch Plan: $0.106 per CU-hour (previously $0.14 per CU-hour)
Scale Plan: $0.222 per CU-hour (previously $0.26 per CU-hour)
Agent Plan: $0.106 per CU-hour (previously $0.14 per CU-hour)

This comes as a result of significant cost savings realized via engineering improvements shipped as we consolidate our storage/compute architecture into Databricks. To be crystal clear, this cost savings comes with no negative impact on performance. In fact over the next few months we will also ship major performance optimizations for all Neon and Lakebase users. We will write about all of them in detail as they are made available.

How this impacts the cost of real-world workloads on Neon:

To show how this impacts your overall costs, we've taken three representative workloads from different customer types on Neon and priced them out on competing platforms.

For an entry-level database. Our pure usage-based pricing gives you the lowest-cost entry for cloud databases. Even if you want to run it always-on, we beat the price of provisioned-resource providers.

For startups -- the benefits of autoscaling and low-cost dev environments make Neon a better price than alternatives. If your business needs SOC2 or HIPAA compliance the savings are more pronounced because we don't charge a high fixed fee for premium features.

How are we able to lower prices?

As we grow, we are able to find efficiencies from scale and optimization. When that happens we have two choices:

Increase our margins - Keep the price consistent and get a higher margin.
Pass the savings on to the customer - lower the price and keep the margin the same.

We choose to pass the savings on because we are building the Postgres layer for the internet, we are not building artisanal database server management. To compare ourselves to retail chains, we aspire to operate like Costco, known for the $1.50 hot dog and selling 50% of the world's cashews, not Erewhon, known for the $20 strawberry.

Better living through distributed architecture

Most traditional Postgres providers are anchored to the price of cloud VM's because their service is essentially giving each customer several managed cloud VMs with Postgres on it. Neon runs as a distributed service with separate storage and compute components. When we started out, we deliberately put off certain cost optimizations to focus instead on user-impacting features and performance. Now that we are consolidating into Databricks infrastructure and scaling up to unprecedented levels, it makes more sense to spend engineering hours on those optimizations.

In short, our architecture plus our unification with Databricks gives us the ability to do a number of things.

Lower cost of operating databases - Part of what we're doing today.
Offer a Free Plan - Scale-to-zero lowers the barrier to entry for databases. We spend less on running our Free Plan than most startups spend on billboards in SF.
Autoscaling for everyone - When storage is handled separately in a distributed system, compute becomes much more fungible. We dynamically adjust compute allocated to workloads millions of times a day to ensure maximum performance and efficiency.
Usable database branching - The separate storage layer is what enables customers to cheaply and instantly create data and schema copies of their database, regardless of size.
Instant everything - Provisioning, point-in-time restore, snapshots... By breaking away from the old \"database on a machine\" model, all of these actions complete in less than a second on Neon.

What do you need next?

If you're just prototyping, you've built something in a weekend and now need to scale it, or you're building the next generation of application infrastructure with AI, we are commoditizing the database layer so you can focus on higher-level work. We won't rest until Neon has a similar level of predictability, operational overhead and cost as S3.

What else would help you scale on Neon? Let us know and we'll follow up with you.

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